Application of Machine Learning in Action Recognition and Action Prediction
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 May 2026 | Viewed by 7
Special Issue Editor
Special Issue Information
Dear Colleagues,
Action recognition and prediction are pivotal research areas in computer vision and machine learning, with significant implications for a wide range of applications such as intelligent surveillance, human–computer interaction, autonomous driving and healthcare. The advancement of supervised learning techniques, particularly deep learning models, has led to remarkable progress in these fields. This Special Issue aims to bring together the latest research and innovations in the application of supervised learning for action recognition and prediction. We seek high-quality, original research papers that address the challenges and explore new frontiers in this domain.
Topics of interest include, but are not limited to:
- Novel supervised deep learning architectures for action recognition and prediction.
- Advanced techniques for feature extraction and representation learning from video data.
- Methods for improving the robustness and generalization of models to unseen environments and subjects.
- Applications of action recognition and prediction in real-world scenarios, such as sports analysis, healthcare monitoring, robotics and augmented reality.
- Techniques for real-time and efficient action recognition and prediction.
- Supervised methods for addressing challenges like complex actions, long-term activities and human–object interactions.
- The use of large-scale annotated datasets and benchmarks for training and evaluating supervised models.
Dr. Jiaqi Lv
Guest Editor
Manuscript Submission Information
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Keywords
- action recognition
- action prediction
- machine learning
- computer vision
- video analysis
- representation learning
- human–object interaction
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